Bạn viết chuẩn Python với kiểu dữ liệu như sau:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

    </server>
    -->
  </servers>

  <!-- mirrors
   | This is a list of mirrors to be used in downloading artifacts from remote repositories.
   |
   | It works like this: a POM may declare a repository to use in resolving certain artifacts.
   | However, this repository may have problems with heavy traffic at times, so people have mirrored
   | it to several places.
   |

You write standard Python with types:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Você escreve Python padrão com tipos:

```Python
from datetime import date

from pydantic import BaseModel

# Declare uma variável como str
# e obtenha suporte do editor dentro da função
def main(user_id: str):
    return user_id


# Um modelo do Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date

          }
        }
      }
    },
    /*
     * This one comes last to work around b/367716565. (One *possible* alternative would be to not
     * declare any methods in this enum, converting assertFailsToDecode into a static method that is
     * implemented with a `switch`. I haven't tested that.)
     */
    @GwtIncompatible // decodingStream(Reader)
    DECODING_STREAM {

///

### Create the `Settings` object { #create-the-settings-object }

Import `BaseSettings` from Pydantic and create a sub-class, very much like with a Pydantic model.

The same way as with Pydantic models, you declare class attributes with type annotations, and possibly default values.

You can use all the same validation features and tools you use for Pydantic models, like different data types and additional validations with `Field()`.

* Vérifier qu'il existe un paramètre de requête facultatif nommé `q` (comme dans `http://127.0.0.1:8000/items/foo?q=somequery`) pour les requêtes `GET`.
    * Puisque le paramètre `q` est déclaré avec `= None`, il est facultatif.
    * Sans le `None`, il serait nécessaire (comme l'est <abbr title="en anglais : body">le corps</abbr> de la requête dans le cas du `PUT`).

  abstract void handleAllCompleted();

  /** Adds the chain to the seen set, and returns whether all the chain was new to us. */
  private static boolean addCausalChain(Set<Throwable> seen, Throwable param) {
    // Declare a "true" local variable so that the Checker Framework will infer nullness.
    Throwable t = param;

    for (; t != null; t = t.getCause()) {
      boolean firstTimeSeen = seen.add(t);
      if (!firstTimeSeen) {

    return startIndex == endIndex
        ? EMPTY
        : new ImmutableLongArray(array, start + startIndex, start + endIndex);
  }

  @IgnoreJRERequirement // used only from APIs that use streams
  /*
   * We declare this as package-private, rather than private, to avoid generating a synthetic
   * accessor method (under -target 8) that would lack the Android flavor's @IgnoreJRERequirement.
   */
  Spliterator.OfLong spliterator() {

    return startIndex == endIndex
        ? EMPTY
        : new ImmutableIntArray(array, start + startIndex, start + endIndex);
  }

  /*
   * We declare this as package-private, rather than private, to avoid generating a synthetic
   * accessor method (under -target 8) that would lack the Android flavor's @IgnoreJRERequirement.
   */
  Spliterator.OfInt spliterator() {